Volume 44 Issue 10
Oct.  2018
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ZHANG Kai, XIONG Jiajun, FU Tingting, et al. Multi-model estimation of HGV based on coupled aerodynamic parameters[J]. Journal of Beijing University of Aeronautics and Astronautics, 2018, 44(10): 2156-2164. doi: 10.13700/j.bh.1001-5965.2018.0028(in Chinese)
Citation: ZHANG Kai, XIONG Jiajun, FU Tingting, et al. Multi-model estimation of HGV based on coupled aerodynamic parameters[J]. Journal of Beijing University of Aeronautics and Astronautics, 2018, 44(10): 2156-2164. doi: 10.13700/j.bh.1001-5965.2018.0028(in Chinese)

Multi-model estimation of HGV based on coupled aerodynamic parameters

doi: 10.13700/j.bh.1001-5965.2018.0028
Funds:

National High-tech Research and Development Program of China 2015AA7326042

National High-tech Research and Development Program of China 2015AA8321471

Foundation for Military Postgraduates of China 2016JY312

More Information
  • Corresponding author: XIONG Jiajun, E-mail:124611796@qq.com
  • Received Date: 12 Jan 2018
  • Accepted Date: 11 May 2018
  • Publish Date: 20 Oct 2018
  • Using aerodynamic parameters to model the unknown aerodynamics is an effective way to improve the tracking accuracy of hypersonic gliding vehicles. The aerodynamic acceleration and its derivative is analyzed to prove the necessity of unknown aerodynamics modeling in this paper. Based on the non-coupled aerodynamic parameter model, two coupled aerodynamic parameter models, the Bank model and the spiral model, are constructed by using the priori information of the aerodynamic acceleration in the turn and pitch directions. The target's state and aerodynamic parameters are estimated by a decomposed estimator, and the state filter and the aerodynamic parameter filter are deduced respectively. Meanwhile, considering the maneuver frequencies of parameters in different flight modes, the interacting multiple model tracking algorithm is built based on the coupled aerodynamic parameters. The simulation results show that the accuracy of the proposed algorithms is significantly higher than other tracking algorithms for such targets. In the meantime, the performance of the bank model is better than that of the spiral model, and its computational complexity is smaller.

     

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